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Predicting Treatment Outcomes in Stage III-IV Colorectal Cancer Patients Based on a Deep Learning Time-Series Analysis Model Combined with Pathology

Predicting Treatment Outcomes in Stage III-IV Colorectal Cancer Patients Based on a Deep Learning Time-Series Analysis Model Combined with Pathology

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600120308
Enrollment
Unknown
Registered
2026-03-12
Start date
2026-03-15
Completion date
Unknown
Last updated
2026-03-16

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Stage III-IV colorectal cancer

Interventions

Observation group:none

Sponsors

the First Affiliated Hospital of Shan Tou University Medical College
Lead Sponsor

Eligibility

Sex/Gender
All
Age
80 Years to 18 Years

Inclusion criteria

Inclusion criteria: 1. Patients diagnosed with stage III-IV colorectal cancer and treated from January 2015 to December 2025; 2. Patients aged 18 to 80 years; 3. Patients with complete clinical data, including baseline abdominal CT scans and at least one follow-up CT scan.

Exclusion criteria

Exclusion criteria: 1. Patients with other serious health conditions, such as severe heart, brain, liver, lung, or kidney diseases; 2. Patients with other primary tumors; 3. Patients with missing baseline or follow-up CT images or inadequate CT quality; 4. Patients who undergo surgery at a hospital other than the leading or participating institution during the treatment process; 5. Patients with postoperative digital pathology slides that are lost or of poor quality.

Design outcomes

Primary

MeasureTime frame
specificity;Calibration curve;Accuracy;Decision Curve Analysis(DCA);Area under curve(AUC);Receiver operating characteristic curve(ROC);Sensitivity;

Countries

China

Contacts

Public ContactXinxin Li

the First Affiliated Hospital of Shan Tou University Medical College

13531268157@139.com+86 13531268157

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Mar 20, 2026